Simon Sheldon R
Division of Pediatric Orthopaedics, Beth Israel Hospital, New York, NY 10003, USA.
J Biomech. 2004 Dec;37(12):1869-80. doi: 10.1016/j.jbiomech.2004.02.047.
The technology supporting the analysis of human motion has advanced dramatically. Past decades of locomotion research have provided us with significant knowledge about the accuracy of tests performed, the understanding of the process of human locomotion, and how clinical testing can be used to evaluate medical disorders and affect their treatment. Gait analysis is now recognized as clinically useful and financially reimbursable for some medical conditions. Yet, the routine clinical use of gait analysis has seen very limited growth. The issue of its clinical value is related to many factors, including the applicability of existing technology to addressing clinical problems; the limited use of such tests to address a wide variety of medical disorders; the manner in which gait laboratories are organized, tests are performed, and reports generated; and the clinical understanding and expectations of laboratory results. Clinical use is most hampered by the length of time and costs required for performing a study and interpreting it. A "gait" report is lengthy, its data are not well understood, and it includes a clinical interpretation, all of which do not occur with other clinical tests. Current biotechnology research is seeking to address these problems by creating techniques to capture data rapidly, accurately, and efficiently, and to interpret such data by an assortment of modeling, statistical, wave interpretation, and artificial intelligence methodologies. The success of such efforts rests on both our technical abilities and communication between engineers and clinicians.
支持人体运动分析的技术已经取得了巨大进步。过去几十年的运动研究为我们提供了关于所执行测试的准确性、对人体运动过程的理解，以及如何利用临床测试来评估医学病症并影响其治疗等方面的重要知识。如今，步态分析在某些医学病症中被认为具有临床实用性且可获得医保报销。然而，步态分析在临床中的常规应用增长非常有限。其临床价值问题涉及许多因素，包括现有技术解决临床问题的适用性；此类测试用于解决各种医学病症的有限性；步态实验室的组织方式、测试的执行方式以及报告的生成方式；以及临床对实验室结果的理解和期望。临床应用受到进行一项研究并解读其结果所需的时间长度和成本的最大阻碍。一份“步态”报告篇幅冗长，其数据难以理解，并且包含临床解读，而其他临床测试则不会出现这些情况。当前的生物技术研究正试图通过创建能够快速、准确且高效地捕捉数据，并通过各种建模、统计、波形解读和人工智能方法来解读此类数据的技术，以解决这些问题。这些努力的成功既取决于我们的技术能力，也取决于工程师与临床医生之间的沟通。
